{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "# user-id = 6278507012\n",
    "df = pd.read_csv('./weibo-crawler/weibo/蜿蜒曲折的盘山公路/6278507012.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['日期'] = pd.to_datetime(df['日期'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fd7b1b3c4a8>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 26085 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py:211: RuntimeWarning: Glyph 26399 missing from current font.\n",
      "  font.set_text(s, 0.0, flags=flags)\n",
      "/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 26085 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n",
      "/anaconda3/lib/python3.7/site-packages/matplotlib/backends/backend_agg.py:180: RuntimeWarning: Glyph 26399 missing from current font.\n",
      "  font.set_text(s, 0, flags=flags)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "res = df.groupby(by=[df[\"日期\"].dt.year, df[\"日期\"].dt.month]).count()['日期']\n",
    "#sco = df.groupby(by=[df[\"日期\"].dt.year, df[\"日期\"].dt.month])['score'].mean()\n",
    "res.plot(kind=\"bar\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, '北京·和平里七区社区', nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, '韶关·中国丹霞山世界地质公园', nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, '舟山·嵊泗枸杞岛青年旅舍', '上海', nan, nan, nan], dtype=object)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array(df['位置'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# user-id = 1846315375\n",
    "df = pd.read_csv('./weibo-crawler/weibo/李嘉轩_astro/1846315375.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "311"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, nan, nan, nan, nan, nan, nan, nan, '蜿蜒曲折的盘山公路', nan, nan, nan,\n",
       "       nan, nan, nan, '蜿蜒曲折的盘山公路', nan, nan, '网易云音乐', nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, '网易云音乐',\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, '知乎', nan, nan,\n",
       "       nan, nan, '网易云音乐', nan, nan, nan, nan, nan, nan, '还是陆任钾', nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, '黑云角闪斜长片麻岩', nan,\n",
       "       '网易云音乐', nan, nan, nan, nan, nan, nan, nan, 'Pirateknife', nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, '网易云音乐', nan,\n",
       "       'Popolarnight', nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, '北京大学', nan, nan, nan, '丁钊翰', nan, '网易云音乐', '北大青天会', nan, nan,\n",
       "       nan, nan, '雷雨心AdoKenTorothy', nan, nan, '网易云音乐', '网易云音乐', nan, nan,\n",
       "       '北京大学', nan, nan, '虾米音乐', 'QQ音乐', '网易云音乐', nan, '网易云音乐', '网易云音乐',\n",
       "       '网易云音乐', 'RAiNBOW计划', nan, nan, nan, nan, '曹俊IHEP', 'QQ音乐',\n",
       "       '网易云音乐', 'QQ音乐', 'QQ音乐', '网易云音乐', nan, '网易云音乐', nan, nan, nan, nan,\n",
       "       nan, '北京大学', '海豚汀布莱克', nan, nan, nan, nan, nan, 'QQ音乐', nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, '李日斤_BJP,Rdairye', nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, '麦野场畔牧歌', nan,\n",
       "       '北京天文馆朱进,北京天文馆詹想,Rdairye,麦野场畔牧歌,M45昴星团,HFer-RB', nan,\n",
       "       '北京天文馆朱进,北京天文馆詹想,老张Nelson,Rdairye,天尼玛居然晴了', nan, nan,\n",
       "       '麦野场畔牧歌,HFer-RB', nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, '拇姬', nan, nan, nan, '北京天文馆詹想,西宁一中陈箐泽',\n",
       "       nan, 'M45昴星团', '微盘', nan, nan, nan, 'WIS护肤', nan, nan, nan, nan,\n",
       "       'Rdairye,肖戴凝,西宁一中陈箐泽', '天文爱好者杂志社', nan, nan, nan], dtype=object)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array(df['@用户'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
